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In this paper, we prospectively review some artificial intelligence (AI) techniques and models used to enhance clinical decisions for patients with corneal diseases and conditions. Cornea subspeciality was a pioneer in aggregating technology to clinical practice. It provided the ability to early diagnose diseases and improve treatments. Currently, we face the challenge of dealing with a tremendous amount of information from complementary multimodal imaging devices. The analysis of such data for enhancing clinical decisions is perfectly suitable for AI. While AI models are rapidly growing in various fields, some are already available and in use by clinicians, for instance to help in refractive surgery screening. AI models represent a boundless method for helping to deal with and avoid the overload of an extraordinary amount of information provided by advances in complementary diagnosis. It is currently ready to use in refractive surgery screening. The challenge is to coordinate multicentre collaborations in order to build good quality and large data collection to train and improve AI models. AI is an instrument to upturn clinical decision power with many possible applications for ophthalmologists.
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Lopes et al. (2019) studied this question.
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